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268 articles for “error model”
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DEM Development using Geographic Information System for Topographic Assessment
Abstract: Topography of the earth surface plays a vital role in the distribution of water within the natural land surfaces. This includes various hydrological processes like surface runoff, infiltration and evaporation. The quantitative assessment of these processes mainly depends upon the topography of the surfaces. Many topographic features can be computed directly from Digital Elevation Model (DEM). Assessment of topography manually is generally tedious, time consuming and often subject to error. …
Published in Journal of Water Resource Engineering and Management · Vol. 1, Issue 3, 2014 · pp. 17–23 Read article
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Statistical Modeling for Weld Quality Assessment using AI SAW Welding of Mild Steel
Abstract: The main issue to the industries that apply Submerged Arc Welding (SAW) is quality assurance since the structural integrity dictates safety and the performance of the industry. The existing system of checking manuals is not only time consuming but also has human errors that make it mandatory to deploy automated intelligent systems. This study carries out an extensive comparison of the leading approaches based on the use of Artificial Intelligence …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 892–907 Read article
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AI-Driven Prediction of Mechanical and Thermal Properties in Polymer-Based Functionally Graded Composites
Abstract: The proposed architecture of the current paper is an artificial intelligence (AI)-driven model of forecasting mechanical and thermal aspects of polymer-based functionally-graded composites (FGCs). Traditional micromechanical and finite element models, which are practical in homogeneous composites, might not be able to account in nonlinear interaction that is caused by compositional gradient. To overcome the challenge, machine learning (ML) models like artificial neural network (ANN), support vectors regression (SVR), and gradient-boosted …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 70–89 Read article
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Fabrication and drilling characterization of Hemp & Grewia-Optiva hybrid composite and comparison with ANN model
Abstract: In recent days the use of natural fibers has increased over synthetic fibers due to various advantages. The alkali treatment for these natural fibers further improves the adhesion between fiber and matrix and greatly enhances the mechanical properties of the composite. The present study involves the fabrication of a hybrid composite using the alkali-treated (5% NaOH concentration) natural fibers – Hemp &Grewia-optiva as reinforcement material and epoxy as a matrix …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 138–146 Read article
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Issues and Challenges for Computing in Embedded System
Abstract: The reliability of any software system is very important for us. As we continue the process of error detection and error correction on the software system, the reliability of the software keeps on increasing. So, for modeling this growth in the reliability of any system, many formulations in the form of Software Reliability Growth Models has been proposed. Among these approaches, maximum approaches are based on NHPP. In this paper, …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 6, Issue 2, 2018 · pp. 18–21 Read article
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Energy conserving Detection Model for cooperative region Attacks in Wireless detector Networks
Abstract: This study describes energy computation algorithmic rule wireless detector networks. The algorithmic rule is adjustable, we are able to wage counter attacks in against either single black holes or groups of malicious nodes within the detector networks. Routing data table (DRI) is employed to traumatize modification and cross checking and knowledge to spot the cooperative region nodes. AHP (Analytic Hierarchy Process): mechanism is employed to mitigate the safety problems concerning …
Published in Journal Of Network security · Vol. 6, Issue 3, 2018 · pp. 18–22 Read article
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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A Comprehensive survey of robust image quality metrics for satellite imagery
Abstract: Satellite imagery is essential for applications like environmental monitoring, urban development, precision agriculture, defence surveillance, and disaster response. The reliability of these applications is closely tied to the quality of the captured images, which may be compromised by atmospheric effects, sensor imperfections, compression artifacts, and transmission noise. As a result, accurate image quality assessment (IQA) is essential to ensure trustworthy analysis and informed decision-making in satellite-based systems. The distinctive properties …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 7–20 Read article
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A Study on Chatter Marks in Crankshaft Pin Grinding Process Using Taguchi Technique
Abstract: Crankshaft pin grinding is a vital machining process in automotive industry. It is a finishing operation to the crankshaft of the engine, which if neglected could lead to a significant cost to the manufacturer of warranty claims. The study aims at identifying significant process parameters that are influencing the chatter marks and also setting the process parameters of the machine to get a good quality product. Chatter marks are the …
Published in Journal of Mechatronics and Automation · Vol. 5, Issue 1, 2018 · pp. 1–5 Read article
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Performance Evaluation of Adaptive MIMO-OFDM System Model for Wireless Networks
Abstract: Enormous growth of wireless technologies and research trends in networking has developed many useful applications. Wireless networks with various protocols and standards are huge in demand because of the expansion of internet of things (IoT). All wireless networks demand for high data rate, low energy consumption, higher throughput, more reliability, better quality of services (QoS) and quality of information (QoI). This paper presents multiple in multiple out (MIMO) orthogonal frequency …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 4, Issue 1, 2017 · pp. 17–23 Read article
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Experimental Validation and Implementation Framework for Optimized Methane Yield Prediction in Anaerobic Digestion
Abstract: The correct validation and realistic application of optimized anaerobic digestion (AD) models are essential steps in transferring biogas production systems to real-life. This paper outlines an experimental validation and deployment pipeline of an AI-optimized model of the methane yield prediction model based on the application of more advanced machine learning and Bayesian optimization methods. Others The validated surrogate-assisted optimization model was tested with controlled laboratory-scale AD experiments at optimized operating …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 25–32 Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing · Vol. 11, Issue 1, 2021 · pp. 9–25 Read article
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Fractional Riemannian Fuzzy C-Means with Time-Series Regularization for Economic Manifold Forecasting
Abstract: A fractional Riemannian fuzzy c-means framework is proposed for uncertain economic forecasting on non-Euclidean data domains. Observations are represented on a Riemannian manifold, cluster centres are intrinsic prototypes, and a latent fuzzy regime signal is regularised by both autoregressive and fractional-memory penalties. The resulting objective couples geometric clustering with time-series consistency, thereby discouraging partitions that are locally plausible but temporally incoherent. Closed-form membership updates, exponential-map centre updates, normal equations for …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 49–55 Read article
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Accuracy Improvement for Propeller Cavitation Noise Prediction Using UDF
Abstract: Recently, there has been an increase in demand for propulsion systems with higher hydrodynamic performance and lower underwater-radiated noise, as environmental issues are gaining more attention in addition to the traditional military necessity. It is important to reduce cavitation noise when designing propellers of the ships, especially for oceanographic research vessels because they use acoustic instruments and cavitation noise can interfere with their operation. It is well known that, when …
Published in Journal of Experimental & Applied Mechanics · Vol. 16, Issue 2, 2025 · pp. 18–26 Read article
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The Transient Performance of Power Line Towers
Abstract: This paper presents a refined approach to the transient analysis of power line towers. Each section of the tower’s steel structure is accurately modeled as a non-uniform transmission line. Among other features, an efficient representation of the towers’ cross-arms as open-ended non-uniform lines and their subsequent approximation by lumped capacitors will be explored. Furthermore, the error introduced by neglecting the presence of the cross-arms, as well as the effect of …
Published in Trends in Electrical Engineering · Vol. 3, Issue 2, 2013 · pp. 20–28 Read article
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RoseRAG-Based Clinical Decision Support System for Precision Medication Safety
Abstract: Medication-related errors remain a major challenge in healthcare, contributing to adverse drug events, increased hospitalization rates, and substantial healthcare costs. Conventional Clinical Decision Support Systems (CDSS) primarily rely on rule-based mechanisms for identifying drug-related problems (DRPs), including drug–drug interactions, contraindications, dosing errors, therapeutic duplication, and medication omissions. Although effective in structured environments, these systems frequently generate excessive context-insensitive alerts, leading to alert fatigue and reduced clinical acceptance. Recent developments in …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Prediction and Comparative Analysis of Thermal Conductivity of Jatropha Oil-based Hybrid Nanofluid by Multivariable Regression and ANN
Abstract: In the present study, a multivariable regression (MR) and artificial neural network (ANN) method was used to predict the thermal conductivity of Jatropha oil-based ZnO-Ag hybrid nanofluid. Firstly, the ZnO-Ag hybrid nanoparticles were synthesized and mixed in the jatropha oil to prepare various nanofluids at different volume concentrations (F) ranging from 0.05 to 0.20%. The stability and thermal conductivity of the prepared nanofluids were investigated. Wide ranges of temperature and …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 32–39 Read article
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Design and Simulation of Discrete Time Multi-Input Multi-Output Optimal Controller to Control Active and Reactive Power of DFIG
Abstract: The control of active and reactive power of doubly-fed induction generator (DFIG) in a large scale wind farm has become an important issue for the improvement of wind energy system to provide efficient and reliable electrical power with safety. The control strategies of active power and reactive power can be classified in two types—direct power control and indirect power control. First control strategy has designed based on the chosen switching …
Published in Trends in Electrical Engineering · Vol. 5, Issue 1, 2015 · pp. 1–11 Read article